Various simple payment services have been launched in the market within a short time, but consumers have failed to keep up with such pace and have begun to face difficulty in their use of such services. The consumers are experiencing a huge confusion in their choice of simple payment services and are also feeling afraid to use the services. Such confusion and trepidation are evidently affecting how consumers accept the simple payment services. Consumers, as a strategy for minimizing confusion in their choices, come to place focus on seeking additional information, and in particular, they tend to rely on information gained by word of mouth. Word-of-mouth information play an important role in offering help to consumers, but while consumers are provided with a massive amount of such information, they, on the other hand, are experiencing more confusion in making choices when they purchase products because of such data abundancy.
This study composed of “Study Model 1” and “Study Model 2” aims to analyze the word-of-mouth behaviors negatively affecting other people shown after consumers experience confusion due to the distinctive characteristics of word-of-mouth information as well as the influence such characteristics have on one’s decision-making process. First, “Study Model 1” explores into how the characteristics (e.g., complexity, overload, uncertainty, and inconsistency) of word-of-mouth information gained through online or off-line research affect consumer confusion (e.g., similarity confusion, overload-confusion, and ambiguous confusion). Moreover, it looks into how such consumer confusion influences negative word-of-mouth activities to find out its effect on other people. Meanwhile, “Study 2” examines how the confusion and distrust that consumers felt in their choices of simple payment services influence their resistance and technology acceptance, and carries out research for understanding consumer behaviors on simple payment services.
Total sample size is Four hundred thirty-five at the beginning, but after deleting those data with many missing values, Four hundred and three data points remains and uses for testing the research model. For data analysis SPSS and Amos are used to test the hypothesis.
The study results in “Study Model 1” show that the characteristics of word-of-mouth information (e.g., complexity, overload, uncertainty, and inconsistency) all had an influence on consumer confusion (e.g., overload-confusion and ambiguous confusion). Complexity and uncertainty were found to have influenced similarity confusion. On the other hand, overload and inconsistency did not have any influence on similarity confusion. In addition, it turned out that ambiguous confusion and overload-confusion all had a positive (+) effect with negative word-of-mouth activities, while similarity confusion did not affect such activities.
The study results in “Study Model 2” show that first, similarity confusion, ambiguous confusion and over-confusion all had a positive (+) effect with distrust but not on resistance. Distrust has a positive (+) effect on resistance. In sum, it can be seen that consumer confusion has an indirect effect on resistance through distrust. Second, similarity confusion and ambiguous confusion all have negative (-) effects on perceived ease of use, and excessive confusion has no positive effect on ease of use. Third, although distrust does not affect both perceived usefulness and intention to use, consumer resistance negatively affects perceived usefulness and intention to use, and perceived ease of use has a negative (-) effect on resistance. In addition, perceived usefulness and perceived ease of use have positive (+) effects on intention to use. It was also found that the perceived ease of use had a positive (+) effect on perceived usefulness.
As seen in the study results, there are cases in which consumers rather face more confusion in their choices because of their searching of word-of-mouth information. In addition, the intermediary role of consumer confusions in the relationship between the characteristics of word-of-mouth information and consumer response was identified. This study has significance in that it complements the lack of consideration for emotional aspects in the existing studies on technology acceptance models, and that it presents an extended model enabling systematic understanding of characteristics on consumers’ word-of-mouth information by including the consumers’ confusion of choices into its scope.